递归查询性能问题
Recursive query performance issues
我有一个来自 geonames 网站 (http://download.geonames.org/export/dump/) 的英国数据库转储。它由大约 60000 条记录组成。
table结构如下：
CREATE TABLE `geoname` (
`geonameid` INT(11) NOT NULL,
`name` VARCHAR(200) NULL DEFAULT NULL,
`asciiname` VARCHAR(200) NULL DEFAULT NULL COLLATE 'utf8_unicode_ci',
`preferredname` VARCHAR(200) NULL DEFAULT NULL,
`alternatenames` VARCHAR(10000) NULL DEFAULT NULL COLLATE `utf8_unicode_ci',
`latitude` DECIMAL(10,7) NULL DEFAULT NULL,
`longitude` DECIMAL(10,7) NULL DEFAULT NULL,
`feature_class` CHAR(1) NULL DEFAULT NULL,
`feature_code` VARCHAR(10) NULL DEFAULT NULL,
`country_code` VARCHAR(2) NULL DEFAULT NULL COLLATE 'utf8_unicode_ci',
`cc2` VARCHAR(60) NULL DEFAULT NULL,
`admin1` VARCHAR(20) NULL DEFAULT NULL COLLATE 'utf8_unicode_ci',
`admin2` VARCHAR(80) NULL DEFAULT NULL COLLATE 'utf8_unicode_ci',
`admin3` VARCHAR(20) NULL DEFAULT NULL,
`admin4` VARCHAR(20) NULL DEFAULT NULL,
`population` INT(11) NULL DEFAULT NULL,
`elevation` INT(11) NULL DEFAULT NULL,
`gtopo30` INT(11) NULL DEFAULT NULL,
`timezone` VARCHAR(40) NULL DEFAULT NULL,
`moddate` DATETIME NULL DEFAULT NULL,
PRIMARY KEY (`geonameid`),
INDEX `geoname_name_idx` (`name`),
INDEX `geoname_preferredname_idx` (`preferredname`),
INDEX `geoname_admin1_idx` (`admin1`),
INDEX `geoname_admin2_idx` (`admin2`),
INDEX `geoname_admin3_idx` (`admin3`),
INDEX `geoname_admin4_idx` (`admin4`),
INDEX `geoname_feature_code_idx` (`feature_code`),
INDEX `geoname_feature_class_idx` (`feature_class`)
)
COLLATE='utf8_general_ci'
ENGINE=InnoDB
;
我已经为要在查询中使用的列添加了索引。该查询用于自动完成功能，但执行时间很长 - 下面的查询花费了 26.72 秒，这对于自动完成功能来说非常差：
mysql> SELECT t0.preferredname,
-> t4.preferredname AS town,
-> t3.preferredname AS county,
-> t2.preferredname AS district,
-> t1.preferredname AS admin1,
-> MIN(t0.geonameid)
-> FROM geoname t0
-> LEFT JOIN geoname t1 ON t1.admin1 = t0.admin1 AND t1.feature_code = 'ADM1'
-> LEFT JOIN geoname t2 ON t2.admin2 = t0.admin2 AND t2.feature_code = 'ADM2'
-> LEFT JOIN geoname t3 ON t3.admin3 = t0.admin3 AND t3.feature_code = 'ADM3'
-> LEFT JOIN geoname t4 ON t4.admin4 = t0.admin4 AND t4.feature_code = 'ADM4'
-> WHERE t0.feature_class IN ('P', 'A')
-> AND t0.preferredname LIKE 'preston%'
-> GROUP BY t0.preferredname,
-> t4.preferredname,
-> t3.preferredname,
-> t2.preferredname,
-> t1.preferredname;
+------------------------------+--------------------+--------------------------------+---------------------+----------+-------------------+
| preferredname | town | county | district | admin1 | MIN(t0.geonameid) |
+------------------------------+--------------------+--------------------------------+---------------------+----------+-------------------+
| Preston | NULL | Ellingham | Northumberland | England | 2639911 |
| Preston | NULL | Preston | District of Rutland | England | 2639914 |
| Preston | NULL | Preston | East Yorkshire | England | 2639913 |
| Preston | NULL | Preston District | Lancashire | England | 2639912 |
| Preston | NULL | Weymouth and Portland District | Dorset | England | 2639922 |
| Preston | Dymock | Forest of Dean District | Gloucestershire | England | 2639916 |
| Preston | Preston | Cotswold District | Gloucestershire | England | 2639918 |
| Preston | Preston | Dover District | Kent | England | 2639920 |
| Preston | Preston | North Hertfordshire District | Hertfordshire | England | 2639917 |
| Preston Bagot | Preston Bagot | Stratford-on-Avon District | Warwickshire | England | 2639910 |
| Preston Bisset | Preston Bissett | Aylesbury Vale | Buckinghamshire | England | 2639909 |
| Preston Bissett | Preston Bissett | Aylesbury Vale | Buckinghamshire | England | 7299788 |
| Preston Brook | NULL | Preston Brook | Borough of Halton | England | 7296534 |
| Preston Candover | Preston Candover | Basingstoke and Deane District | Hampshire | England | 2639908 |
| Preston Capes | Preston Capes | Daventry District | Northamptonshire | England | 2639907 |
| Preston District | NULL | Preston District | Lancashire | England | 7290581 |
| Preston Gubbals | NULL | Pimhill | Shropshire | England | 2639906 |
| Preston on Stour | Preston on Stour | Stratford-on-Avon District | Warwickshire | England | 7299630 |
| Preston on the Hill | NULL | Preston Brook | Borough of Halton | England | 2639904 |
| Preston on Wye | NULL | Preston on Wye | Herefordshire | England | 2639903 |
| Preston Park | NULL | NULL | Brighton and Hove | England | 2639921 |
| Preston Patrick | Preston Patrick | South Lakeland District | Cumbria | England | 7298113 |
| Preston Richard | Preston Richard | South Lakeland District | Cumbria | England | 7300167 |
| Preston Road | NULL | Brent | Greater London | England | 2639919 |
| Preston St Mary | Preston St. Mary | Babergh District | Suffolk | England | 2639915 |
| Preston St. Mary | Preston St. Mary | Babergh District | Suffolk | England | 7301329 |
| Preston upon the Weald Moors | NULL | Preston upon the Weald Moors | Telford and Wrekin | England | 2639900 |
| Preston Wynne | NULL | Preston Wynne | Herefordshire | England | 2639899 |
| Preston-on-Tees | NULL | Preston-on-Tees | Stockton-on-Tees | England | 7299560 |
| Preston-under-Scar | Preston-under-Scar | Richmondshire District | North Yorkshire | England | 7291664 |
| Prestonpans | NULL | NULL | East Lothian | Scotland | 2639902 |
+------------------------------+--------------------+--------------------------------+---------------------+----------+-------------------+
31 rows in set (26.72 sec)
mysql>
当我在上述查询中使用探查器时，我得到以下信息：
mysql> select substring_index(event_name,'/',-1) as Status, truncate((timer_end-timer_start)/1000000000000,6) as Duration from performance_schema.events_stages_history_long where event_id>=8215932 and event_id<=9810811;
+----------------------+-----------+
| Status | Duration |
+----------------------+-----------+
| starting | 0.000198 |
| checking permissions | 0.000004 |
| checking permissions | 0.000001 |
| checking permissions | 0.000001 |
| checking permissions | 0.000001 |
| checking permissions | 0.000005 |
| Opening tables | 0.000044 |
| init | 0.000088 |
| System lock | 0.000013 |
| optimizing | 0.000022 |
| statistics | 0.075318 |
| preparing | 0.000059 |
| Creating tmp table | 0.000082 |
| Sorting result | 0.000014 |
| executing | 0.000003 |
| Sending data | 24.472337 |
| Creating sort index | 0.000292 |
| end | 0.000007 |
| query end | 0.000022 |
| removing tmp table | 0.000118 |
| closing tables | 0.000024 |
| freeing items | 0.000278 |
| cleaning up | 0.000001 |
+----------------------+-----------+
23 rows in set (0.00 sec)
当 运行 使用 Explain 的查询时，我得到以下信息：
mysql> EXPLAIN SELECT t0.preferredname,
-> t4.preferredname AS town,
-> t3.preferredname AS county,
-> t2.preferredname AS district,
-> t1.preferredname AS admin1,
-> MIN(t0.geonameid)
-> FROM geoname t0
-> LEFT JOIN geoname t1 ON t1.admin1 = t0.admin1 AND t1.feature_code = 'ADM1'
-> LEFT JOIN geoname t2 ON t2.admin2 = t0.admin2 AND t2.feature_code = 'ADM2'
-> LEFT JOIN geoname t3 ON t3.admin3 = t0.admin3 AND t3.feature_code = 'ADM3'
-> LEFT JOIN geoname t4 ON t4.admin4 = t0.admin4 AND t4.feature_code = 'ADM4'
-> WHERE t0.feature_class IN ('P', 'A')
-> AND t0.preferredname LIKE 'preston%'
-> GROUP BY t0.preferredname,
-> t4.preferredname,
-> t3.preferredname,
-> t2.preferredname,
-> t1.preferredname;
+----+-------------+-------+------------+-------+-----------------------------------------------------+---------------------------+---------+----------------------+------+----------+---------------------------------------------------------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-------+------------+-------+-----------------------------------------------------+---------------------------+---------+----------------------+------+----------+---------------------------------------------------------------------+
| 1 | SIMPLE | t0 | NULL | range | geoname_preferredname_idx,geoname_feature_class_idx | geoname_preferredname_idx | 603 | NULL | 55 | 70.01 | Using index condition; Using where; Using temporary; Using filesort |
| 1 | SIMPLE | t1 | NULL | ref | geoname_admin1_idx,geoname_feature_code_idx | geoname_feature_code_idx | 33 | const | 4 | 100.00 | Using where |
| 1 | SIMPLE | t2 | NULL | ref | geoname_admin2_idx,geoname_feature_code_idx | geoname_feature_code_idx | 33 | const | 185 | 100.00 | Using where |
| 1 | SIMPLE | t3 | NULL | ref | geoname_admin3_idx,geoname_feature_code_idx | geoname_admin3_idx | 63 | test.t0.admin3 | 14 | 100.00 | Using where |
| 1 | SIMPLE | t4 | NULL | ref | geoname_admin4_idx,geoname_feature_code_idx | geoname_admin4_idx | 63 | test.t0.admin4 | 7 | 100.00 | Using where |
+----+-------------+-------+------------+-------+-----------------------------------------------------+---------------------------+---------+----------------------+------+----------+---------------------------------------------------------------------+
5 rows in set, 1 warning (0.06 sec)
请注意，我使用的是 group by 子句，因为数据的子级别名称重复。
如何优化此查询？任何建议提示和技巧将不胜感激。
我猜你希望检索匹配用户提供的不完整搜索字符串的地点，然后加入行政管辖区以提供信息更丰富的自动完成功能。
这里的技巧是快速检索候选地点。像这样的子查询就可以了。
SELECT geonameid, preferredname, admin1, admin2, admin3, admin4
FROM geonames
WHERE feature_class IN ('P', 'A')
AND preferredname LIKE 'preston%'
这是查找操作的核心。它可以通过
上的复合覆盖索引来加速
CREATE INDEX lookup1
ON geonames(feature_class, preferredname, admin1, admin2, admin3, admin4);
试试这个查询。看看它对你来说是否足够快（亚秒级）。如果不是，请尝试此变体：
SELECT geonameid, preferredname, admin1, admin2, admin3, admin4
FROM geonames
WHERE feature_class ='P'
AND preferredname LIKE 'preston%'
UNION ALL
SELECT geonameid, preferredname, admin1, admin2, admin3, admin4
FROM geonames
WHERE feature_class ='A'
AND preferredname LIKE 'preston%'
MySQL 的查询规划器可以随机访问索引到第一个符合条件的行，然后通过顺序扫描索引检索所需的所有内容。
然后，您在 JOIN 操作中使用该子查询的结果集。现在，您只需处理联接中少量的相关行，而不是整个混乱。
SELECT t0.preferredname,
t4.preferredname AS town,
t3.preferredname AS county,
t2.preferredname AS district,
t1.preferredname AS admin1,
MIN(t0.geonameid) geonameid
FROM (
SELECT geonameid, preferredname, admin1, admin2, admin3, admin4
FROM geonames
WHERE feature_class IN ='P'
AND preferredname LIKE 'preston%'
UNION ALL
SELECT geonameid, preferredname, admin1, admin2, admin3, admin4
FROM geonames
WHERE feature_class ='A'
AND preferredname LIKE 'preston%'
) t0
LEFT JOIN geoname t1 ON t1.admin1 = t0.admin1 AND t1.feature_code = 'ADM1'
LEFT JOIN geoname t2 ON t2.admin2 = t0.admin2 AND t2.feature_code = 'ADM2'
LEFT JOIN geoname t3 ON t3.admin3 = t0.admin3 AND t3.feature_code = 'ADM3'
LEFT JOIN geoname t4 ON t4.admin4 = t0.admin4 AND t4.feature_code = 'ADM4'
GROUP BY t0.preferredname,
t4.preferredname,
t3.preferredname,
t2.preferredname,
t1.preferredname
专业提示：很多单列索引很少能加速具有多个过滤条件的查询，尤其是使用范围过滤器，例如LIKE 'something%'。适当的多列索引更有帮助。
我认为你应该先改变你的 table。
列 asciiname、feature_class、feature_code、country_code、cc2、adminN、timezone 的排序规则应该更改为 latin1_general_ci。这将减少数据和索引的数据存储要求，并允许服务器在执行查询时在缓冲区中容纳更多数据。
您必须将 population 数据类型更改为 INTEGER UNSIGNED，因为当前您的数据可能已针对某些记录进行了截断（检查 'Commonwealth of Nations' 的值）。
您还可以考虑将 moddate 更改为 DATE，将 elevation 和 gtopo30 更改为 SMALLINT 以进一步减少存储需求。
然后您需要将索引 geoname_admin1_idx 更改为：
INDEX `geoname_admin1_idx` (`admin1`)
至：
INDEX `geoname_admin1_idx` (`feature_code`, `admin1`)
对其他 geoname_adminN_idx 索引执行相同的操作。
这将允许服务器更快地在查询中进行连接。
仅这些更改就产生了巨大的差异，并且在不修改查询的情况下将我系统上的查询执行时间从 8 秒减少到几乎为零（0.1 秒）。
解释这些修改后的结果：
mysql> explain
-> SELECT t0.preferredname,
-> t4.preferredname AS town,
-> t3.preferredname AS county,
-> t2.preferredname AS district,
-> t1.preferredname AS admin1
-> , MIN(t0.geonameid)
-> FROM geoname t0
-> LEFT JOIN geoname t1 ON t1.admin1 = t0.admin1 AND t1.feature_code = 'ADM1'
-> LEFT JOIN geoname t2 ON t2.admin2 = t0.admin2 AND t2.feature_code = 'ADM2'
-> LEFT JOIN geoname t3 ON t3.admin3 = t0.admin3 AND t3.feature_code = 'ADM3'
-> LEFT JOIN geoname t4 ON t4.admin4 = t0.admin4 AND t4.feature_code = 'ADM4'
-> WHERE t0.feature_class IN ('P', 'A')
-> AND t0.preferredname LIKE 'preston%'
-> GROUP BY t0.preferredname,
-> t4.preferredname,
-> t3.preferredname,
-> t2.preferredname,
-> t1.preferredname;
+----+-------------+-------+------------+-------+-----------------------------------------------------------------------------+---------------------------+---------+----------------------+------+----------+---------------------------------------------------------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-------+------------+-------+-----------------------------------------------------------------------------+---------------------------+---------+----------------------+------+----------+---------------------------------------------------------------------+
| 1 | SIMPLE | t0 | NULL | range | geoname_preferredname_idx,geoname_feature_class_idx | geoname_preferredname_idx | 803 | NULL | 55 | 68.74 | Using index condition; Using where; Using temporary; Using filesort |
| 1 | SIMPLE | t1 | NULL | ref | geoname_admin1_idx,geoname_admin2_idx,geoname_admin3_idx,geoname_admin4_idx | geoname_admin2_idx | 13 | const | 4 | 100.00 | Using where |
| 1 | SIMPLE | t2 | NULL | ref | geoname_admin1_idx,geoname_admin2_idx,geoname_admin3_idx,geoname_admin4_idx | geoname_admin2_idx | 96 | const,test.t0.admin2 | 10 | 100.00 | NULL |
| 1 | SIMPLE | t3 | NULL | ref | geoname_admin1_idx,geoname_admin2_idx,geoname_admin3_idx,geoname_admin4_idx | geoname_admin3_idx | 36 | const,test.t0.admin3 | 4 | 100.00 | NULL |
| 1 | SIMPLE | t4 | NULL | ref | geoname_admin1_idx,geoname_admin2_idx,geoname_admin3_idx,geoname_admin4_idx | geoname_admin4_idx | 36 | const,test.t0.admin4 | 3 | 100.00 | NULL |
+----+-------------+-------+------------+-------+-----------------------------------------------------------------------------+---------------------------+---------+----------------------+------+----------+---------------------------------------------------------------------+
检查 key_len、ref、行和额外加入 tables。
您使用的查询也可能受益于索引 (feature_class, preferredname)。
这是用索引解释：
+----+-------------+-------+------------+-------+------------------------------------------------------------------------------------------------------+-----------------------------------------+---------+----------------------+------+----------+--------------------------------------------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-------+------------+-------+------------------------------------------------------------------------------------------------------+-----------------------------------------+---------+----------------------+------+----------+--------------------------------------------------------+
| 1 | SIMPLE | t0 | NULL | range | geoname_preferredname_idx,geoname_feature_class_idx,geoname_feature_class_preferredname_idx | geoname_feature_class_preferredname_idx | 805 | NULL | 42 | 100.00 | Using index condition; Using temporary; Using filesort |
| 1 | SIMPLE | t1 | NULL | ref | geoname_admin1_idx,geoname_admin2_idx,geoname_admin3_idx,geoname_admin4_idx,geoname_feature_code_idx | geoname_admin2_idx | 13 | const | 4 | 100.00 | Using where |
| 1 | SIMPLE | t2 | NULL | ref | geoname_admin1_idx,geoname_admin2_idx,geoname_admin3_idx,geoname_admin4_idx,geoname_feature_code_idx | geoname_admin2_idx | 96 | const,test.t0.admin2 | 12 | 100.00 | NULL |
| 1 | SIMPLE | t3 | NULL | ref | geoname_admin1_idx,geoname_admin2_idx,geoname_admin3_idx,geoname_admin4_idx,geoname_feature_code_idx | geoname_admin3_idx | 36 | const,test.t0.admin3 | 4 | 100.00 | NULL |
| 1 | SIMPLE | t4 | NULL | ref | geoname_admin1_idx,geoname_admin2_idx,geoname_admin3_idx,geoname_admin4_idx,geoname_feature_code_idx | geoname_admin4_idx | 36 | const,test.t0.admin4 | 3 | 100.00 | NULL |
+----+-------------+-------+------------+-------+------------------------------------------------------------------------------------------------------+-----------------------------------------+---------+----------------------+------+----------+--------------------------------------------------------+
我有一个来自 geonames 网站 (http://download.geonames.org/export/dump/) 的英国数据库转储。它由大约 60000 条记录组成。
table结构如下：
CREATE TABLE `geoname` (
`geonameid` INT(11) NOT NULL,
`name` VARCHAR(200) NULL DEFAULT NULL,
`asciiname` VARCHAR(200) NULL DEFAULT NULL COLLATE 'utf8_unicode_ci',
`preferredname` VARCHAR(200) NULL DEFAULT NULL,
`alternatenames` VARCHAR(10000) NULL DEFAULT NULL COLLATE `utf8_unicode_ci',
`latitude` DECIMAL(10,7) NULL DEFAULT NULL,
`longitude` DECIMAL(10,7) NULL DEFAULT NULL,
`feature_class` CHAR(1) NULL DEFAULT NULL,
`feature_code` VARCHAR(10) NULL DEFAULT NULL,
`country_code` VARCHAR(2) NULL DEFAULT NULL COLLATE 'utf8_unicode_ci',
`cc2` VARCHAR(60) NULL DEFAULT NULL,
`admin1` VARCHAR(20) NULL DEFAULT NULL COLLATE 'utf8_unicode_ci',
`admin2` VARCHAR(80) NULL DEFAULT NULL COLLATE 'utf8_unicode_ci',
`admin3` VARCHAR(20) NULL DEFAULT NULL,
`admin4` VARCHAR(20) NULL DEFAULT NULL,
`population` INT(11) NULL DEFAULT NULL,
`elevation` INT(11) NULL DEFAULT NULL,
`gtopo30` INT(11) NULL DEFAULT NULL,
`timezone` VARCHAR(40) NULL DEFAULT NULL,
`moddate` DATETIME NULL DEFAULT NULL,
PRIMARY KEY (`geonameid`),
INDEX `geoname_name_idx` (`name`),
INDEX `geoname_preferredname_idx` (`preferredname`),
INDEX `geoname_admin1_idx` (`admin1`),
INDEX `geoname_admin2_idx` (`admin2`),
INDEX `geoname_admin3_idx` (`admin3`),
INDEX `geoname_admin4_idx` (`admin4`),
INDEX `geoname_feature_code_idx` (`feature_code`),
INDEX `geoname_feature_class_idx` (`feature_class`)
)
COLLATE='utf8_general_ci'
ENGINE=InnoDB
;
我已经为要在查询中使用的列添加了索引。该查询用于自动完成功能，但执行时间很长 - 下面的查询花费了 26.72 秒，这对于自动完成功能来说非常差：
mysql> SELECT t0.preferredname,
-> t4.preferredname AS town,
-> t3.preferredname AS county,
-> t2.preferredname AS district,
-> t1.preferredname AS admin1,
-> MIN(t0.geonameid)
-> FROM geoname t0
-> LEFT JOIN geoname t1 ON t1.admin1 = t0.admin1 AND t1.feature_code = 'ADM1'
-> LEFT JOIN geoname t2 ON t2.admin2 = t0.admin2 AND t2.feature_code = 'ADM2'
-> LEFT JOIN geoname t3 ON t3.admin3 = t0.admin3 AND t3.feature_code = 'ADM3'
-> LEFT JOIN geoname t4 ON t4.admin4 = t0.admin4 AND t4.feature_code = 'ADM4'
-> WHERE t0.feature_class IN ('P', 'A')
-> AND t0.preferredname LIKE 'preston%'
-> GROUP BY t0.preferredname,
-> t4.preferredname,
-> t3.preferredname,
-> t2.preferredname,
-> t1.preferredname;
+------------------------------+--------------------+--------------------------------+---------------------+----------+-------------------+
| preferredname | town | county | district | admin1 | MIN(t0.geonameid) |
+------------------------------+--------------------+--------------------------------+---------------------+----------+-------------------+
| Preston | NULL | Ellingham | Northumberland | England | 2639911 |
| Preston | NULL | Preston | District of Rutland | England | 2639914 |
| Preston | NULL | Preston | East Yorkshire | England | 2639913 |
| Preston | NULL | Preston District | Lancashire | England | 2639912 |
| Preston | NULL | Weymouth and Portland District | Dorset | England | 2639922 |
| Preston | Dymock | Forest of Dean District | Gloucestershire | England | 2639916 |
| Preston | Preston | Cotswold District | Gloucestershire | England | 2639918 |
| Preston | Preston | Dover District | Kent | England | 2639920 |
| Preston | Preston | North Hertfordshire District | Hertfordshire | England | 2639917 |
| Preston Bagot | Preston Bagot | Stratford-on-Avon District | Warwickshire | England | 2639910 |
| Preston Bisset | Preston Bissett | Aylesbury Vale | Buckinghamshire | England | 2639909 |
| Preston Bissett | Preston Bissett | Aylesbury Vale | Buckinghamshire | England | 7299788 |
| Preston Brook | NULL | Preston Brook | Borough of Halton | England | 7296534 |
| Preston Candover | Preston Candover | Basingstoke and Deane District | Hampshire | England | 2639908 |
| Preston Capes | Preston Capes | Daventry District | Northamptonshire | England | 2639907 |
| Preston District | NULL | Preston District | Lancashire | England | 7290581 |
| Preston Gubbals | NULL | Pimhill | Shropshire | England | 2639906 |
| Preston on Stour | Preston on Stour | Stratford-on-Avon District | Warwickshire | England | 7299630 |
| Preston on the Hill | NULL | Preston Brook | Borough of Halton | England | 2639904 |
| Preston on Wye | NULL | Preston on Wye | Herefordshire | England | 2639903 |
| Preston Park | NULL | NULL | Brighton and Hove | England | 2639921 |
| Preston Patrick | Preston Patrick | South Lakeland District | Cumbria | England | 7298113 |
| Preston Richard | Preston Richard | South Lakeland District | Cumbria | England | 7300167 |
| Preston Road | NULL | Brent | Greater London | England | 2639919 |
| Preston St Mary | Preston St. Mary | Babergh District | Suffolk | England | 2639915 |
| Preston St. Mary | Preston St. Mary | Babergh District | Suffolk | England | 7301329 |
| Preston upon the Weald Moors | NULL | Preston upon the Weald Moors | Telford and Wrekin | England | 2639900 |
| Preston Wynne | NULL | Preston Wynne | Herefordshire | England | 2639899 |
| Preston-on-Tees | NULL | Preston-on-Tees | Stockton-on-Tees | England | 7299560 |
| Preston-under-Scar | Preston-under-Scar | Richmondshire District | North Yorkshire | England | 7291664 |
| Prestonpans | NULL | NULL | East Lothian | Scotland | 2639902 |
+------------------------------+--------------------+--------------------------------+---------------------+----------+-------------------+
31 rows in set (26.72 sec)
mysql>
当我在上述查询中使用探查器时，我得到以下信息：
mysql> select substring_index(event_name,'/',-1) as Status, truncate((timer_end-timer_start)/1000000000000,6) as Duration from performance_schema.events_stages_history_long where event_id>=8215932 and event_id<=9810811;
+----------------------+-----------+
| Status | Duration |
+----------------------+-----------+
| starting | 0.000198 |
| checking permissions | 0.000004 |
| checking permissions | 0.000001 |
| checking permissions | 0.000001 |
| checking permissions | 0.000001 |
| checking permissions | 0.000005 |
| Opening tables | 0.000044 |
| init | 0.000088 |
| System lock | 0.000013 |
| optimizing | 0.000022 |
| statistics | 0.075318 |
| preparing | 0.000059 |
| Creating tmp table | 0.000082 |
| Sorting result | 0.000014 |
| executing | 0.000003 |
| Sending data | 24.472337 |
| Creating sort index | 0.000292 |
| end | 0.000007 |
| query end | 0.000022 |
| removing tmp table | 0.000118 |
| closing tables | 0.000024 |
| freeing items | 0.000278 |
| cleaning up | 0.000001 |
+----------------------+-----------+
23 rows in set (0.00 sec)
当 运行 使用 Explain 的查询时，我得到以下信息：
mysql> EXPLAIN SELECT t0.preferredname,
-> t4.preferredname AS town,
-> t3.preferredname AS county,
-> t2.preferredname AS district,
-> t1.preferredname AS admin1,
-> MIN(t0.geonameid)
-> FROM geoname t0
-> LEFT JOIN geoname t1 ON t1.admin1 = t0.admin1 AND t1.feature_code = 'ADM1'
-> LEFT JOIN geoname t2 ON t2.admin2 = t0.admin2 AND t2.feature_code = 'ADM2'
-> LEFT JOIN geoname t3 ON t3.admin3 = t0.admin3 AND t3.feature_code = 'ADM3'
-> LEFT JOIN geoname t4 ON t4.admin4 = t0.admin4 AND t4.feature_code = 'ADM4'
-> WHERE t0.feature_class IN ('P', 'A')
-> AND t0.preferredname LIKE 'preston%'
-> GROUP BY t0.preferredname,
-> t4.preferredname,
-> t3.preferredname,
-> t2.preferredname,
-> t1.preferredname;
+----+-------------+-------+------------+-------+-----------------------------------------------------+---------------------------+---------+----------------------+------+----------+---------------------------------------------------------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-------+------------+-------+-----------------------------------------------------+---------------------------+---------+----------------------+------+----------+---------------------------------------------------------------------+
| 1 | SIMPLE | t0 | NULL | range | geoname_preferredname_idx,geoname_feature_class_idx | geoname_preferredname_idx | 603 | NULL | 55 | 70.01 | Using index condition; Using where; Using temporary; Using filesort |
| 1 | SIMPLE | t1 | NULL | ref | geoname_admin1_idx,geoname_feature_code_idx | geoname_feature_code_idx | 33 | const | 4 | 100.00 | Using where |
| 1 | SIMPLE | t2 | NULL | ref | geoname_admin2_idx,geoname_feature_code_idx | geoname_feature_code_idx | 33 | const | 185 | 100.00 | Using where |
| 1 | SIMPLE | t3 | NULL | ref | geoname_admin3_idx,geoname_feature_code_idx | geoname_admin3_idx | 63 | test.t0.admin3 | 14 | 100.00 | Using where |
| 1 | SIMPLE | t4 | NULL | ref | geoname_admin4_idx,geoname_feature_code_idx | geoname_admin4_idx | 63 | test.t0.admin4 | 7 | 100.00 | Using where |
+----+-------------+-------+------------+-------+-----------------------------------------------------+---------------------------+---------+----------------------+------+----------+---------------------------------------------------------------------+
5 rows in set, 1 warning (0.06 sec)
请注意，我使用的是 group by 子句，因为数据的子级别名称重复。
如何优化此查询？任何建议提示和技巧将不胜感激。
我猜你希望检索匹配用户提供的不完整搜索字符串的地点，然后加入行政管辖区以提供信息更丰富的自动完成功能。
这里的技巧是快速检索候选地点。像这样的子查询就可以了。
SELECT geonameid, preferredname, admin1, admin2, admin3, admin4
FROM geonames
WHERE feature_class IN ('P', 'A')
AND preferredname LIKE 'preston%'
这是查找操作的核心。它可以通过
上的复合覆盖索引来加速CREATE INDEX lookup1
ON geonames(feature_class, preferredname, admin1, admin2, admin3, admin4);
试试这个查询。看看它对你来说是否足够快（亚秒级）。如果不是，请尝试此变体：
SELECT geonameid, preferredname, admin1, admin2, admin3, admin4
FROM geonames
WHERE feature_class ='P'
AND preferredname LIKE 'preston%'
UNION ALL
SELECT geonameid, preferredname, admin1, admin2, admin3, admin4
FROM geonames
WHERE feature_class ='A'
AND preferredname LIKE 'preston%'
MySQL 的查询规划器可以随机访问索引到第一个符合条件的行，然后通过顺序扫描索引检索所需的所有内容。
然后，您在 JOIN 操作中使用该子查询的结果集。现在，您只需处理联接中少量的相关行，而不是整个混乱。
SELECT t0.preferredname,
t4.preferredname AS town,
t3.preferredname AS county,
t2.preferredname AS district,
t1.preferredname AS admin1,
MIN(t0.geonameid) geonameid
FROM (
SELECT geonameid, preferredname, admin1, admin2, admin3, admin4
FROM geonames
WHERE feature_class IN ='P'
AND preferredname LIKE 'preston%'
UNION ALL
SELECT geonameid, preferredname, admin1, admin2, admin3, admin4
FROM geonames
WHERE feature_class ='A'
AND preferredname LIKE 'preston%'
) t0
LEFT JOIN geoname t1 ON t1.admin1 = t0.admin1 AND t1.feature_code = 'ADM1'
LEFT JOIN geoname t2 ON t2.admin2 = t0.admin2 AND t2.feature_code = 'ADM2'
LEFT JOIN geoname t3 ON t3.admin3 = t0.admin3 AND t3.feature_code = 'ADM3'
LEFT JOIN geoname t4 ON t4.admin4 = t0.admin4 AND t4.feature_code = 'ADM4'
GROUP BY t0.preferredname,
t4.preferredname,
t3.preferredname,
t2.preferredname,
t1.preferredname
专业提示：很多单列索引很少能加速具有多个过滤条件的查询，尤其是使用范围过滤器，例如LIKE 'something%'。适当的多列索引更有帮助。
我认为你应该先改变你的 table。
列 asciiname、feature_class、feature_code、country_code、cc2、adminN、timezone 的排序规则应该更改为 latin1_general_ci。这将减少数据和索引的数据存储要求，并允许服务器在执行查询时在缓冲区中容纳更多数据。
您必须将 population 数据类型更改为 INTEGER UNSIGNED，因为当前您的数据可能已针对某些记录进行了截断（检查 'Commonwealth of Nations' 的值）。
您还可以考虑将 moddate 更改为 DATE，将 elevation 和 gtopo30 更改为 SMALLINT 以进一步减少存储需求。
然后您需要将索引 geoname_admin1_idx 更改为：
INDEX `geoname_admin1_idx` (`admin1`)
至：
INDEX `geoname_admin1_idx` (`feature_code`, `admin1`)
对其他 geoname_adminN_idx 索引执行相同的操作。 这将允许服务器更快地在查询中进行连接。
仅这些更改就产生了巨大的差异，并且在不修改查询的情况下将我系统上的查询执行时间从 8 秒减少到几乎为零（0.1 秒）。
解释这些修改后的结果：
mysql> explain
-> SELECT t0.preferredname,
-> t4.preferredname AS town,
-> t3.preferredname AS county,
-> t2.preferredname AS district,
-> t1.preferredname AS admin1
-> , MIN(t0.geonameid)
-> FROM geoname t0
-> LEFT JOIN geoname t1 ON t1.admin1 = t0.admin1 AND t1.feature_code = 'ADM1'
-> LEFT JOIN geoname t2 ON t2.admin2 = t0.admin2 AND t2.feature_code = 'ADM2'
-> LEFT JOIN geoname t3 ON t3.admin3 = t0.admin3 AND t3.feature_code = 'ADM3'
-> LEFT JOIN geoname t4 ON t4.admin4 = t0.admin4 AND t4.feature_code = 'ADM4'
-> WHERE t0.feature_class IN ('P', 'A')
-> AND t0.preferredname LIKE 'preston%'
-> GROUP BY t0.preferredname,
-> t4.preferredname,
-> t3.preferredname,
-> t2.preferredname,
-> t1.preferredname;
+----+-------------+-------+------------+-------+-----------------------------------------------------------------------------+---------------------------+---------+----------------------+------+----------+---------------------------------------------------------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-------+------------+-------+-----------------------------------------------------------------------------+---------------------------+---------+----------------------+------+----------+---------------------------------------------------------------------+
| 1 | SIMPLE | t0 | NULL | range | geoname_preferredname_idx,geoname_feature_class_idx | geoname_preferredname_idx | 803 | NULL | 55 | 68.74 | Using index condition; Using where; Using temporary; Using filesort |
| 1 | SIMPLE | t1 | NULL | ref | geoname_admin1_idx,geoname_admin2_idx,geoname_admin3_idx,geoname_admin4_idx | geoname_admin2_idx | 13 | const | 4 | 100.00 | Using where |
| 1 | SIMPLE | t2 | NULL | ref | geoname_admin1_idx,geoname_admin2_idx,geoname_admin3_idx,geoname_admin4_idx | geoname_admin2_idx | 96 | const,test.t0.admin2 | 10 | 100.00 | NULL |
| 1 | SIMPLE | t3 | NULL | ref | geoname_admin1_idx,geoname_admin2_idx,geoname_admin3_idx,geoname_admin4_idx | geoname_admin3_idx | 36 | const,test.t0.admin3 | 4 | 100.00 | NULL |
| 1 | SIMPLE | t4 | NULL | ref | geoname_admin1_idx,geoname_admin2_idx,geoname_admin3_idx,geoname_admin4_idx | geoname_admin4_idx | 36 | const,test.t0.admin4 | 3 | 100.00 | NULL |
+----+-------------+-------+------------+-------+-----------------------------------------------------------------------------+---------------------------+---------+----------------------+------+----------+---------------------------------------------------------------------+
检查 key_len、ref、行和额外加入 tables。
您使用的查询也可能受益于索引 (feature_class, preferredname)。 这是用索引解释：
+----+-------------+-------+------------+-------+------------------------------------------------------------------------------------------------------+-----------------------------------------+---------+----------------------+------+----------+--------------------------------------------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-------+------------+-------+------------------------------------------------------------------------------------------------------+-----------------------------------------+---------+----------------------+------+----------+--------------------------------------------------------+
| 1 | SIMPLE | t0 | NULL | range | geoname_preferredname_idx,geoname_feature_class_idx,geoname_feature_class_preferredname_idx | geoname_feature_class_preferredname_idx | 805 | NULL | 42 | 100.00 | Using index condition; Using temporary; Using filesort |
| 1 | SIMPLE | t1 | NULL | ref | geoname_admin1_idx,geoname_admin2_idx,geoname_admin3_idx,geoname_admin4_idx,geoname_feature_code_idx | geoname_admin2_idx | 13 | const | 4 | 100.00 | Using where |
| 1 | SIMPLE | t2 | NULL | ref | geoname_admin1_idx,geoname_admin2_idx,geoname_admin3_idx,geoname_admin4_idx,geoname_feature_code_idx | geoname_admin2_idx | 96 | const,test.t0.admin2 | 12 | 100.00 | NULL |
| 1 | SIMPLE | t3 | NULL | ref | geoname_admin1_idx,geoname_admin2_idx,geoname_admin3_idx,geoname_admin4_idx,geoname_feature_code_idx | geoname_admin3_idx | 36 | const,test.t0.admin3 | 4 | 100.00 | NULL |
| 1 | SIMPLE | t4 | NULL | ref | geoname_admin1_idx,geoname_admin2_idx,geoname_admin3_idx,geoname_admin4_idx,geoname_feature_code_idx | geoname_admin4_idx | 36 | const,test.t0.admin4 | 3 | 100.00 | NULL |
+----+-------------+-------+------------+-------+------------------------------------------------------------------------------------------------------+-----------------------------------------+---------+----------------------+------+----------+--------------------------------------------------------+